Improved robust multiuser detection in non-Gaussian channels

Abstract

Abstract-In many wireless systems where multiuser detection techniques may be applied, the ambient channel noise is known through experimental measurements to be decidedly nonGaussian, due largely to impulsive phenomena. The performance of many multiuser detectors can degrade substantially in the presence of such impulsive ambient noise. In this paper, we develop robust multiuser detection techniques for combating multipleaccess interference and impulsive noise in CDMA communication systems. These techniques are based on the M-estimation method for robust regression. Analytical and simulation results show that the proposed robust techniques offer significant performance gain over linear multiuser detectors in impulsive noise, with little attendant increase in computational complexity.We also develop a subspace-based technique for blind adaptive implementation of the robust multiuser detectors, which requires only the signature waveform and the timing of the desired user in order to demodulate that user's signal. The robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels.

A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment

“…The scope of this paper is to robustify the Kalman-filter-based detector to a general framework of non-Gaussian state and measurement noises. The proposed study yields to two novel algorithms which are able to correct the impulsive noise without clipping the received signal as is done in many previous works [29,30,31,32,41].…”

“…We propose here to reject the impulses rather than to clip them as is done in many previous works [29,30,31,32,41]. In this case, the transmitted symbol estimation at this iteration is taken from the adjacent decided state vector via the proposed feedback.…”

“…We suggest to incorporate a decision feedback in order to generate the required replicas of the corrupted symbols by operating on the adjacent state vectors which have been decided earlier (and assuming the decision to be correct). We, therefore, propose to reject the samples corrupted by the impulsive noise rather than to clip them as is done in many previous works [22,28,29,30,31,32]. By adapting the transition equation to the number of successive corrupted samples, we can reestimate the corrupted symbols of the users by exploiting the proposed feedback.…”

Blind Detection of Synchronous CDMA in Non-Gaussian Channels

“…(23) for the data vectors, we treat the transmitted vectors as continuous variables first and then project the estimation results onto discrete sets. With additional computational cost, it is possible to achieve improved performance by using enumeration or a slowest descent algorithm [13] to estimate .…”

“…Suboptimal multiuser detectors have also been proposed for these channels [12], [13]. In this paper, we address the problem of blind source separation in non-Gaussian ambient noise.…”